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Aim and Scope

Urban Mobility deals with movement of passengers and goods in the highly complex urban setting. This is becoming increasingly critical as we march toward the smart city era. The goal of research is to advance the state-of-the-art on Intelligent Transportation Systems in cities where the challenges multiply from noisy signals, highly dynamic traffic events resulting from changing demands, closures and accidents, multiple modes of transport, personalized preferences, and many traffic movements, e.g., commute, personal, touristic, services, etc.

This special issue intends to bring together transdisciplinary researchers and practitioners working in topics from multiple areas, e.g., Data Mining, Machine Learning, Algorithms, Numerical Optimization, Public Transport, City Planning, and Traffic Engineering among others. The ultimate goal of this venue is to evaluate not only the theoretical contributions of the data-driven methodology proposed in each research work, but also its potential deployment/impact as well as its advances with respect to the State-of-the-Art/State-of-the-Practice in the domains of the related applications.

The journal welcomes articles on any of the above topics or closely related disciplines in the context of urban mobility. TSAS will encourage original submissions that have not been published or submitted in any form elsewhere, and submissions which may significantly contribute to opening up new and potentially important areas of research and development. TSAS will publish outstanding papers that are "major value-added extensions" of papers previously published in conferences. Such extensions should contribute at least 30% new original work. In this case, authors will need to identify in a separate document the list of extensions over their previously published paper. For more information, please visit https://tsas.acm.org/authors.cfm or contact the special-issue guest-editor at [email protected].